The discrimination or evaluation of an odor is generally performed based on the olfactory sense of a human being. This requires consideration of the fact that there are personal differences among those (a panel) who actually smell the odor and that their olfactory senses vary according to their physical condition of the day. Therefore, in order to obtain an accurate and objective result, it is necessary to ensure that the panel contains an adequate number of persons and to pay proper attention to the atmosphere of the testing location and other factors, which requires a substantial amount of time and labor. Additionally, even if such matters are given attention, it is difficult to constantly obtain a definitive determination at a certain standard because of the fact that the olfactory sense of a human being tends to adapt to an odor.
To solve such problems, odor discriminating apparatuses have been developed that use odor sensors which react to odorous substances. These odor discriminating apparatuses obtain detection signals from plural odor sensors having different characteristics and process the detection signals employing a multivariate analysis, such as cluster analysis or principal component analysis, or non-linear analysis using a neural network. As a result, the odor discriminating apparatuses can determine the distances between the odors of plural samples (i.e. whether or not these odors belong to the same or similar categories).
Another recently developed odor discriminating apparatus evaluates the odor of a sample gas in terms of both the quality and strength, and respectively quantifies them (refer to Patent Document 1, for example). An example of evaluating the difference of the quality of odors among a plurality of samples using such an odor discriminating apparatus is described with reference to FIG. 6. The odor of one sample is set as a reference odor, and that of another sample as a subject odor. In a multidimensional odor space formed by the detection signals from a plurality of odor sensors having different characteristics, the measurement point Q which represents the measurement result of the reference odor, and the measurement point P which represents the measurement result of the subject odor, are plotted. For easer understanding, the odor space in FIG. 6 is a two-dimensional odor space formed by the detection signals from two odors sensors. The reference odor vector S1, directed from the origin to the measurement point Q of the reference odor, and the subject odor vector Sx, directed from the origin to the measurement point P of the subject odor, are determined. Then, the angle θ between the two vectors is obtained. Since each vector shows a direction specific to its odor, if the angle θ is small, the two odors belong to the same or similar categories. Conversely, if the angle θ is large, they belong to different categories.
Sensors using oxide semiconductors, which are generally employed in an odor discriminating apparatus, show a non-linear response to the change in the concentration. Therefore, such non-linearity should be taken into account when actually analyzing measurement data. That is, if the relationship between the concentration of an odor component and its detection signal is linear in each odor sensor, the odor vectors have a linear shape as shown in FIG. 6. However, in sensors using metal oxide semiconductors, the relationship between the concentration of an odor component and its detection signal is not linear, and the non-linearity is different for each sensor. Hence, the odor vectors have a curved shape. That is, when an odor having the same quality but having different concentrations are measured, the locus of the measurement points will have a curved shape. Regarding this question, when the difference in the quality of odors between different samples is to be evaluated, conventionally, the influence of the concentration is canceled as follows. As shown in FIG. 7, the concentration of a reference odor is incrementally changed and the data is measured at, for example, three points. Then, a curve along the measured points a1, a1, and a3 is created. This curve is called a reference odor curve H1. The similarity is determined as follows. First, a line perpendicular to the reference odor curve H1 is drawn from the measurement point P of a sample measured. The foot of the perpendicular line on the reference odor curve is denoted as K. Then, the length of the perpendicular line, i.e. the distance dmin between the measurement point P and the point K, is computed, and the length L of the reference odor curve H1 from the origin to the point K is also computed. Subsequently, the angle θ is computed using the following equation:tan θ=dmin/L. Based on the value of the angle θ, the similarity of the odor qualities is computed.